mirror of
https://github.com/facebookresearch/fairseq.git
synced 2024-09-11 17:25:31 +03:00
fbd4cef9a5
Summary: - fairseq can now be installed via pip: `pip install fairseq` - command-line tools are globally accessible: `fairseq-preprocess`, `fairseq-train`, `fairseq-generate`, etc. Pull Request resolved: https://github.com/pytorch/fairseq/pull/495 Differential Revision: D14017761 Pulled By: myleott fbshipit-source-id: 10c9f6634a3056074eac2f33324b4f1f404d4235
35 lines
1.0 KiB
ReStructuredText
35 lines
1.0 KiB
ReStructuredText
.. role:: hidden
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:class: hidden-section
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.. _Learning Rate Schedulers:
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Learning Rate Schedulers
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========================
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Learning Rate Schedulers update the learning rate over the course of training.
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Learning rates can be updated after each update via :func:`step_update` or at
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epoch boundaries via :func:`step`.
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.. automodule:: fairseq.optim.lr_scheduler
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:members:
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.. autoclass:: fairseq.optim.lr_scheduler.FairseqLRScheduler
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:members:
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:undoc-members:
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.. autoclass:: fairseq.optim.lr_scheduler.cosine_lr_scheduler.CosineSchedule
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:members:
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:undoc-members:
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.. autoclass:: fairseq.optim.lr_scheduler.fixed_schedule.FixedSchedule
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:members:
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:undoc-members:
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.. autoclass:: fairseq.optim.lr_scheduler.inverse_square_root_schedule.InverseSquareRootSchedule
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:members:
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:undoc-members:
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.. autoclass:: fairseq.optim.lr_scheduler.reduce_lr_on_plateau.ReduceLROnPlateau
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:members:
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:undoc-members:
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.. autoclass:: fairseq.optim.lr_scheduler.triangular_lr_scheduler.TriangularSchedule
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:members:
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:undoc-members:
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